AIMC Topic: Algorithms

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The fifth era of science: Artificial scientific intelligence.

PLoS biology
The era of artificial scientific intelligence is here. As algorithms generate discoveries at scale, what role remains for human scientists?

A plaque recognition algorithm for coronary OCT images by Dense Atrous Convolution and attention mechanism.

PloS one
Currently, plaque segmentation in Optical Coherence Tomography (OCT) images of coronary arteries is primarily carried out manually by physicians, and the accuracy of existing automatic segmentation techniques needs further improvement. To furnish eff...

Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance.

PloS one
In this study, we address the inherent challenges in radiotherapy (RT) plan quality assessment (QA). RT, a prevalent cancer treatment, utilizes high-energy beams to target tumors while sparing adjacent healthy tissues. Typically, an RT plan is refine...

Automated Vessel Occlusion Software in Acute Ischemic Stroke: Pearls and Pitfalls.

Stroke
Software programs leveraging artificial intelligence to detect vessel occlusions are now widely available to aid in stroke triage. Given their proprietary use, there is a surprising lack of information regarding how the software works, who is using t...

Machine learning algorithms integrate bulk and single-cell RNA data to reveal the crosstalk and heterogeneity of NOTCH and autophagy activity following idiopathic pulmonary fibrosis.

International immunopharmacology
BACKGROUND: NOTCH and autophagy significantly impact the pathogenesis of idiopathic pulmonary fibrosis (IPF); however, studies exploring their heterogeneity and potential correlation at the single-cell level are still lacking. Identifying the feature...

ADC-MambaNet: a lightweight U-shaped architecture with mamba and multi-dimensional priority attention for medical image segmentation.

Biomedical physics & engineering express
Medical image segmentation is becoming a growing crucial step in assisting with disease detection and diagnosis. However, medical images often exhibit complex structures and textures, resulting in the need for highly complex methods. Particularly, wh...

Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

PloS one
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...

BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers.

PloS one
Bangla news floods the web, and the need for smarter and more efficient classification techniques is greater than ever. Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever-growing c...

TempODEGraphNet: predicting user churn using dynamic social graphs and neural ODEs.

PloS one
Research on user churn prediction has been conducted across various domains for a long time. Among these, the gaming domain is characterized by its potential for diverse types of interactions between users. Due to this characteristic, many studies on...

Enhanced pedestrian trajectory prediction via overlapping field-of-view domains and integrated Kolmogorov-Arnold networks.

PloS one
Accurate pedestrian trajectory prediction is crucial for applications such as autonomous driving and crowd surveillance. This paper proposes the OV-SKTGCNN model, an enhancement to the Social-STGCNN model, aimed at addressing its low prediction accur...